Abstract

The aetiology of autism is unknown, although prenatal exposures have been
the focus of epidemiological research for over 40 years.

Aims

To provide the first quantitative review and meta-analysis of the
association between maternal pregnancy complications and pregnancy-related
factors and risk of autism.

Method

PubMed, Embase and PsycINFO databases were searched for epidemiological
studies that examined the association between pregnancy-related factors and
autism. Forty studies were eligible for inclusion in the meta-analysis.
Summary effect estimates were calculated for factors examined in multiple
studies.

Results

Over 50 prenatal factors have been examined. The factors associated with
autism risk in the meta-analysis were advanced parental age at birth, maternal
prenatal medication use, bleeding, gestational diabetes, being first born
v. third or later, and having a mother born abroad. The factors with
the strongest evidence against a role in autism risk included previous fetal
loss and maternal hypertension, proteinuria, pre-eclampsia and swelling.

Conclusions

There is insufficient evidence to implicate any one prenatal factor in
autism aetiology, although there is some evidence to suggest that exposure to
pregnancy complications may increase the risk.

Autism is a developmental disorder characterised by deficits in social
interaction and communication, and restricted, repetitive interests and
behaviours beginning in infancy and toddler
years.1,2
The prevalence of autism has been estimated at 13/10 000 and is believed to be
rising.3 The
aetiology is unknown. Although the estimated 60–92% concordance rate in
monozygotic twins as compared with 0–10% in dizygotic twins underscores
the importance of genetic influences, the incomplete concordance in
monozygotic twins also indicates a role of environmental
factors.4,5
It is now believed that the mechanism underlying autism aetiology is most
likely polygenic and potentially epistatic and that environmental factors may
interact with genetic factors to increase
risk.6,7

Although the distinctive neuropathology remains elusive, studies have shown
macroscopic, microscopic and functional brain
abnormalities.6,8
These brain abnormalities suggest that the aetiologically relevant period may
be in utero because the pathogenesis may begin during the prenatal
period.6

Pregnancy-related exposures have been the focus of a significant amount of
epidemiological research on possible risk factors for autism. Although many
studies support the hypothesis that obstetrical complications may increase the
risk of autism,9 the
specific complications, magnitude of effect and overall conclusions of these
studies are inconsistent. These inconsistencies may be because of
methodological variations including diagnostic criteria, comparison groups,
sample size and exposure assessment methods.

The purpose of this study is to provide a systematic review and
meta-analysis of the epidemiological literature on the relationship between
prenatal complications/exposures and autism. A review article by Kolevson and
colleagues discussed seven studies on this
topic.9 Our study
expands upon this review by providing the first formal meta-analysis as well
as a quantitative review of all 64 studies of prenatal risk factors for autism
published up to March 2007. We review the evidence for all prenatal factors
examined in the literature, and provide a summary effect estimate for all
factors examined in two or more studies. The scope of literature reviewed
allows for meta-regression analyses to examine whether study design
characteristics explain the heterogeneity in results across studies.

Method

Data sources and review methods

PubMed, Embase, and PsycINFO databases were searched using the keywords ‘
autism’ in combination with ‘prenatal’ or ‘
perinatal’ or ‘pregnancy’ or ‘neonatal’,
limited to peer-reviewed studies published in any language through to March
2007. The search identified 698 studies in PubMed, 176 in Embase and 416 in
PsycInfo. The literature search sought to identify all epidemiological studies
that have examined the association of pregnancy and delivery factors and
neonatal complications to the risk of autism. Based on a review of all
abstracts, 83 papers were identified as potentially relevant and reviewed
further. Those studies that were not reviewed included case series, animal
studies, autism prevalence studies, medical hypotheses, studies of other
psychiatric diseases (e.g. schizophrenia) and studies of unrelated exposures
(e.g. demographics, familial psychiatric diseases, genetics, infant
behaviours). Forty-one additional potential papers were identified after
screening the reference lists of original and review articles. Among the 124
studies that were reviewed, we excluded those that did not include a
comparison group (n = 13) or any formal statistical analyses
(n = 3), did not examine exposures during pregnancy or the first
month of life (n = 10), grouped their autism cases with other
childhood psychotic disorders (n = 15) and were review or commentary
articles (n = 18). The control group had to be non-autistic but could
be otherwise affected. In total, 65 studies were eligible for
inclusion5,10–73
in the quantitative review. Two
studies15,30
reporting on the same data-set were considered together, resulting in 64
studies for review.

Although the literature search covered the scope of prenatal, perinatal and
neonatal factors, the current report reviews the pregnancy-related factors
only, and a future publication will address factors related to labour and
delivery as well as neonatal complications in relation to autism. However, it
is important to recognise that prenatal, perinatal and neonatal complications
are interrelated, and are therefore difficult to disentangle and reliably
categorise. Many perinatal and neonatal complications are often the result of
both observed and unobserved prenatal insults and compromises to fetal
development. This report focuses on those potential risk factors that were
commonly identified as being specifically related to the prenatal period in
the extant literature.

The first author abstracted each article on two separate occasions spaced 1
year apart. For each study the following information was recorded:

study results, including indicators of statistical significance, prevalence
of exposures among cases and controls, rates or risks of autism across
exposure levels, relative risks (RRs) and 95% confidence intervals (CIs).

Studies were classified as prospective v. retrospective if
exposures were assessed and recorded before or after the onset of autism,
regardless of when they were analysed for the purposes of the given study. For
the quantitative review, we counted the number of studies that examined each
prenatal factor in relation to the risk of autism and the number of null
findings, significant and marginally significant positive findings,
significant and marginally significant negative findings.

Statistical analysis

Meta-analysis

Of the 64 studies reviewed, 40 were appropriate for inclusion in the
meta-analysis.10–49
Twenty-four studies were excluded from the meta-analysis because they did not
report relative risks and confidence intervals or did not provide information
needed to calculate them. A separate meta-analysis was conducted for each
exposure variable that was examined in two or more studies. For each exposure,
a summary effect estimate was calculated using a random-effects
model.74 Because
power to detect heterogeneity is low in meta-analyses such as
these,75 we took a
conservative approach and used random-effects models to form confidence
intervals, because random-effects models account for any observed
heterogeneity regardless of whether the heterogeneity is statistically
significant. When available, the estimate used for each study was the
multivariate estimate controlling for the maximum number of covariates.

If an effect estimate was reported without the corresponding 95% CI, the
confidence bounds were derived from the P-value provided. If no
P-value was provided, then a P-value of 0.05 or 0.50 was
assumed for factors that did and did not reach statistical significance
respectively.

Several studies included autism-spectrum disorders in their case
definition. Five studies reported results for both the broader phenotype and
for narrowly-defined
autism,22,25–27,29
in which case the study-specific exposure effect estimates using the narrowest
diagnostic criteria were recorded.

The relationships between autism and maternal/paternal age at birth as well
as birth order were assessed categorically and meta-analytic tests of trend
(details available from the authors on
request)76 were
conducted using ordinal categorical variables with the score of each category
equal to the mid-point of the exposure range, using SAS version 9 on UNIX (SAS
Institute, Cary, NC). These trend tests were restricted to studies that
provided information on the number of cases and participants at each exposure
level.

As a result of the rarity of many of the exposures and small sample sizes,
there were tables in some (<5%) of the meta-analyses with zero cell counts.
In these instances, 0.5 was added to each cell of the 2 × 2
table.77

Several studies used multiple control groups (e.g. individuals with
intellectual disability (also known as mental retardation) and healthy
controls). In these studies, the comparison groups were pooled and compared
with the cases as a single group.

Some studies classified the exposures of interest into distinct
subcategories (e.g. bleeding by trimester). In addition to providing a summary
estimate for the primary exposure of interest (e.g. pregnancy bleeding), we
also calculated summary estimates for each subcategory. If only the crude
estimates were provided then the exposures were pooled by simply adding the
cases–controls who experienced each subcategory type. If multivariate
adjusted estimates were provided then the adjusted estimates for each exposure
subcategory were combined using the method proposed by Greenland &
Longnecker76 to
adjust the variance of the summary estimate by accounting for the covariance
due to the inclusion of overlapping comparison groups across exposure
subcategories.

Meta-regression

For each risk factor assessed in multiple studies we examined the
heterogeneity in the relative risks estimated across studies using the Q
statistic.74,78
As a result of the limited power of this
test75 a liberal
P of <0.10 was used to identify meta-analyses that required
further examination to assess potential sources of heterogeneity. If we found
evidence of suggested heterogeneity, a
meta-regression79,80
was conducted to identify measured methodological factors that could explain
the between-study variability (i.e. between-study effect modification).

The analyses of effect modification were conducted using the ‘
metareg’ command in Stata 8 on
Windows.79 The
study characteristics that were examined included: diagnostic criteria
(inclusion of spectrum disorders: yes v. no); exposure information
quality (0, retrospective exposure assessment; 1, mix of retrospective and
prospective exposure assessment; 2, prospective exposure assessment); control
for confounding (0, univariate analysis; 1, control for select demographic
factors, birth order, or IQ; 2, full multivariate analysis or matching with
sibling controls); normal v. abnormal controls; and case selection
(clinic based v. population based). If effect modification was
suggested for a given study characteristic (P<0.10), then a
stratified analysis was performed.

Publication bias was assessed for each factor by conducting tests for
funnel plot
asymmetry81 using
the ‘metabias’ command in Stata 8. Two statistical approaches were
used to examine the association between study size and the effect of the
exposure: the Begg
test82 and the
Egger test.83

Results

Table 1 and
Table 2 list the prenatal
factors that were not included in the meta-analysis due to unavailability of
two or more effect estimates and 95% CIs, as well as an indication of whether
they were associated with autism in the studies in which they were examined.
Online Table DS1 lists the prenatal factors included in the meta-analyses, as
well as the number of null findings, significant and marginally significant
positive findings, and significant and marginally significant negative
findings (protective association). For each factor that was examined in the
meta-analysis, online Table DS1 reports the summary effect estimate and 95% CI
from the random-effects model, and the P-value for the test of
heterogeneity.

Pregnancy-related risk factors examined in multiple studiesa
but not eligible for meta-analysis

The meta-analysis found few statistically significant risk factors.
Maternal gestational diabetes was associated with a two-fold increased risk of
autism. In addition, a significant 81% elevated risk was observed in relation
to maternal bleeding during pregnancy. Maternal medication use was also
associated with a 46% increased risk. Although 15 studies examined the
relationship between prenatal medication use and risk of autism, the majority
studied the general use of any medications during pregnancy, whereas only a
few examined the association with specific classes of medications. A
meta-analysis of the two studies that looked specifically at psychiatric
medication use during pregnancy suggested a significant positive association
with the risk of autism (RR = 1.68).

Maternal age at birth over 30 was associated with an increased risk with
effect estimates ranging from a 27% increased risk (30–34 v.
25–29) to a 106% increase in risk (40+ v. <30). Thirteen
studies were included in the meta-analyses of maternal age at birth. The trend
test included nine studies and indicated a significant increase in risk of
autism with increasing maternal age at birth (trend P = 0.02). A
5-year increase in maternal age was associated with a 7% increase in risk.

Increased paternal age at birth was also found to be a significant risk
factor (trend P = 0.004), with a 5-year increase in paternal age
associated with a 3.6% increase in risk. Individual exposure category effect
estimates ranged from 1.24 (30–39 v. <30) to 1.44 (40+
v. 25–29). In addition, the three studies that examined the
effect of young paternal age at birth indicated a 26% decrease in risk for
paternal age <25 v. 25–29. Only four studies were included
in the meta-analyses of paternal age.

Of the nine studies that indicated a significant relationship between birth
order/parity and risk of autism, six indicated a mixed trend. Specifically,
autism was associated with being first or later born (≥third), often
depending on the size of the sibship. The meta-analysis found a statistically
significant 61% increase in risk for first-born children compared with
children born third or later. This meta-analysis included four studies. No
significant associations were observed in the comparisons of other birth order
categories and the trend test did not indicate a linear relationship between
birth order and autism risk.

Maternal birth abroad was marginally associated with risk of autism. In the
five studies included in the meta-analysis, maternal birth abroad was
associated with a 28% increased risk (P = 0.06). However, the
definition of ‘abroad’ varied as the studies were conducted in
different countries and areas of the world. In the studies conducted in Nordic
countries, a statistically significant 58% increased risk of autism was
observed among the offspring of mothers born abroad.

Heterogeneity in effect estimates across studies was observed for the
following factors (P<0.10): infections during pregnancy,
nausea/vomiting, bleeding, weight gain, maternal age at birth, paternal age at
birth (40+ v. <30), birth order, smoking during pregnancy, mother
born abroad and pre-eclampsia. Table
3 shows the results of the regression analyses that examined the
potential between-study sources of heterogeneity.

The analysis of infections during pregnancy indicated significant effect
modification based on control for covariates. Exposure to intrauterine
infections was associated with a significant increase in risk for autism in
the analysis limited to the four studies that controlled for multiple
covariates or used sibling controls. However, there was no relationship
between infections during pregnancy and autism in the studies that did not
control for covariates or use sibling controls. For nausea/vomiting, there was
significant effect modification based on whether the exposure was assessed
prospectively or retrospectively. The positive relationship between
nausea/vomiting and autism was only significant among prospective studies (RR
= 1.48, 95% CI 1.03–2.14). In fact, the meta-analysis restricted to the
three retrospective studies that examined nausea/vomiting in relation to
autism suggested a protective association (RR = 0.55, 95% CI
0.31–0.98).

The test for linear trend in birth order indicated significant
heterogeneity across studies that could not be explained by variation in any
of the study characteristics examined. The analyses of several maternal age at
birth comparisons as well as the linear trend test also indicated
heterogeneity in the effect estimates across studies. Variation in the
methodological characteristics could not explain the heterogeneity in the
trend estimates. However, heterogeneity in the effect estimates for the
maternal age categorical comparisons may have been as a result of the control
for covariates. In general, the elevation in risk observed in relation to
older maternal age at birth was slightly attenuated in the studies that
controlled for multiple covariates.

Heterogeneity in the effect estimates for maternal smoking during pregnancy
may have been as a result of the study base (population based or clinic
based). No significant relationship with autism was observed overall or within
strata, although only five studies were included in this meta-analysis.

Lastly, for the analyses of toxaemia/pre-eclampsia (17 studies), maternal
birth abroad (5 studies) and bleeding (13 studies), the heterogeneity of
effect estimates across studies could not be explained by any of the study
characteristics investigated.

Publication bias was assessed for all factors examined in three or more
studies. Significant publication bias was only suggested for smoking during
pregnancy (Begg’s test P = 0.03, Egger’s test P
= 0.04). The test for publication bias for prenatal smoking in fact indicated
a potential bias in the direction of publishing inverse associations, as
suggested by the fact that the three (out of five) smaller studies in the
meta-analysis all reported relative risks that were below the null. Both of
the tests for publication bias lacked power because of the small number of
studies included in each
meta-analysis.84
However, as a result of the many tests of publication bias performed it is
likely that we would observe one or more significant results due to chance
alone.

Several studies examined the relationship between compromised prenatal
health in general and risk of autism, although none provided the necessary
data for inclusion in the meta-analysis. Specifically, six studies utilised
prenatal optimality scales to assess the number of prenatal complications
experienced in cases and controls (Gillberg Optimality
Scale,55,61
modified Gillberg Optimality
Scale,41,53
Lewis-Murray
Scale,44 Rochester
Research Obstetrical
Scale60). Four of
these studies reported a significant association between reduced prenatal
optimality and risk of
autism.53,55,60,61

Discussion

This study is the first meta-analysis of the relationship between prenatal
factors and risk of autism. Over 50 prenatal factors have been studied in
relation to autism in 64 epidemiological studies, of which 40 were eligible
for meta-analysis. However, few factors have been examined in multiple
well-conducted studies. Therefore, attempted replication in methodologically
strong studies remains necessary. Although the majority of factors examined in
multiple studies have given inconsistent results, the preponderance of
findings overall have not been statistically significant. The factors with the
strongest evidence for an association with autism risk included advanced
maternal and paternal age at birth, maternal gestational bleeding, gestational
diabetes, being first born v. third or later, maternal prenatal
medication use and maternal birth abroad. The factors with the strongest
evidence against a role in autism risk included previous fetal loss and
maternal pre-eclampsia, proteinuria, hypertension and swelling.

Although there is insufficient evidence to implicate any one prenatal
factor in autism aetiology, the studies using prenatal optimality scales
provide some evidence to suggest that exposure to pregnancy complications in
general may increase the risk of autism. It is also important to note that the
aetiological importance of the prenatal period may not be fully captured by
examining only those complications and characteristics that are manifested and
observed during the period of gestation. Many perinatal and neonatal
complications also reflect what was occurring during pregnancy, and it may be
that only those compromises to the prenatal environment that are manifested in
labour and delivery as well as neonatal health complications are
aetiologically relevant. The potential effects of a non-optimal prenatal
environment as manifested in perinatal and neonatal complications will be
addressed in our subsequent manuscript on this topic.

Parental age

The current meta-analysis shows that increased maternal and paternal age at
birth are both associated with an elevated risk of autism. The biological
mechanisms underlying these relationships are not known. Maternal age may be
associated with autism because of the increased risk of chromosomal
abnormalities in ova of increased age or as a result of unstable trinucleotide
repeats.9 Although
advanced maternal age has been shown to be associated with an increased risk
of obstetrical
complications,85,86
it is unknown which, if any, of these complications may affect the risk of
autism. Reichenberg et
al42 suggested
that the relationship between paternal age and autism may be because of
imprinted genes, de novo spontaneous mutations that accumulate with
advancing age in spermatagonia or confounding by sociocultural environmental
factors. Maternal and paternal age at birth are likely
correlated87,88
and many of the studies included did not adjust paternal age for maternal age
and vice versa. It is possible that advanced age of both parents plays a role
in the susceptibility to autism or perhaps only maternal age or paternal age
is aetiologically relevant. There is evidence to suggest that paternal age may
be more important. Of the four studies that controlled for the age of the
co-parent, three found only a significant association for paternal age at
birth,33,34,42
and one found only a significant association for maternal
age.38 When the
analysis of maternal age was restricted to the four studies that controlled
for paternal age the relative risk for a 5-year increase in maternal age was
1.06 (P = 0.08). All studies of paternal age included in the
meta-analysis were adjusted for maternal age.

Birth order

Perhaps the factor that was most commonly associated with the risk of
autism in the literature was birth order. Nine studies reported a significant
relationship between birth order/parity and autism. However, the nature of the
relationship was inconsistent across studies and was generally not found to be
linear. The difficulty in elucidating the relationship between birth
order/parity and autism may be as a result of potential effect modification by
sibship size, as individuals with autism are more likely to be first-born in
sibship sizes of two and later-born in families with larger sibship
sizes.61,69
The latter trend has been attributed to parents deciding not to have
additional children after one has developed
autism.89

Maternal birth abroad

Maternal immigration has also been highlighted as a potential risk factor
for autism.9 In the
meta-analysis, the elevated risk of autism among the offspring of women born
abroad was just shy of statistical significance. In the three studies
conducted in Nordic countries there was a significant 58% increased risk among
the offspring of mothers born abroad, although the definition and
categorisation of ‘abroad’ differed across the studies. The
strength of the association in the Nordic studies may be because of an unknown
mechanism particular to this area, or, perhaps more likely, may have been as a
result of the methodological strengths of these three studies.

Several hypotheses have been postulated, including the idea that fathers
with social disability potentially as a result of a genetic mechanism
associated with autism may be less able to find a spouse from their own
country and may therefore find a wife from a foreign country with whom to have
children.90 More
likely, Gillberg et
al90 suggested
that women born in another country may not be immunised against the common
infectious agents in the country in which she gives birth and may therefore be
more susceptible to relatively innocuous infections that may increase the risk
for autism. Other possible explanations include a potential role of maternal
stress because of the demands of residing in a new country, particularly with
limited social support, or stress resulting from the experience of emigrating,
perhaps as a result of economic or social factors. These hypotheses do not
explain the relationship with maternal place of birth seen in a cohort study
of children born in California between 1989 and
1994,16 which
showed a 40% decreased risk of autism among the children of women born in
Mexico as compared with California. The association between maternal
immigration and autism risk requires further examination in other areas of the
world to examine whether the relationship can truly be generalised.

Gestational bleeding

Fetal hypoxia may underlie a potential relationship between gestational
bleeding and autism. Maternal bleeding is one of several complications
believed to be associated with fetal
hypoxia.9 Fetal
distress, maternal hypertension, prolonged labour, cord complications, low
Apgar score and Caesarean delivery are other pregnancy-related factors that
are believed to be related to hypoxia and have been associated with autism
risk in some, but not all, studies. Although some brain abnormalities observed
in individuals with autism may reflect a potential role of oxygen deprivation
during development, this possibility requires further examination. Hypoxia has
also been shown to increase dopaminergic activity, and there is evidence for
dopamine overactivation in
autism.91

Bleeding in the second half of pregnancy in particular may reflect severe
complications including placenta praevia or abruptio
placenta.29
Although the analyses stratified by trimester did not produce significant
associations, only two studies were available to calculate the
trimester-specific estimates.

Gestational diabetes

A biological mechanism underlying the potential elevated risk of autism
associated with gestational diabetes is unknown. Gestational diabetes has been
associated with various adverse pregnancy
outcomes,92–94
and the hormonal and metabolic abnormalities and oxidative stress because of
gestational diabetes may have lasting consequences for offspring health and
development.92,95
It is possible that the reported increasing maternal and paternal age at birth
and rate of gestational diabetes may be contributing factors to the rising
prevalence of
autism.96

Medication use

The mechanism underlying the suggested association with maternal medication
use is also unclear because of the variety of medications consumed during
pregnancy and assessed in these studies. Although many medications may cross
the placenta and affect fetal development, the current analysis cannot
indicate which medications may be detrimental. However, the meta-analysis of
two studies that looked at psychiatric medication use suggested a significant
68% increased risk of autism, and one small Croatian
study32 suggested a
higher frequency of hormone use among the mothers of individuals with autism
than among the mothers of controls with intellectual disability (mental
retardation). Maimburg &
Vaeth38 found a 50%
increased risk of autism associated with maternal use of medicine in a
population-based case–control study using Danish national registries.
Although they observed no significant association for anti-epileptics,
antihypertensives, cardiovascular drugs, tocolytics, nor use of steroids, a
significant 60% increased risk of autism was observed in relation to use of
psychoactive drugs. The association with maternal use of psychoactive drugs
may reflect either an effect of the medication exposure, an adverse effect of
the actual treated condition itself on fetal development (confounding by
indication) or transmission of genetic traits possibly shared between autism
and other psychiatric disorders.

Non-causal hypotheses

Investigators have questioned the causal nature of the observed
relationship between prenatal complications and autism. Confounding by birth
order has been suggested, as an increased risk of autism and obstetrical
complications are often observed in first-, fourth- and later-born
offspring.52,73
Although some studies have shown that associations were attenuated and no
longer significant after adjusting for
parity,41,61
other studies have shown that the positive relationship
persists.52,73
A second non-causal hypothesis is that obstetrical complications occur as a
result of the autistic condition in the offspring or as a consequence of other
factors (e.g. genetic factors) that are the true causal determinants of
autism.52 In this
epiphenomena explanation, pregnancy complications simply reflect the
abnormalities of autistic fetal development, or the same familial factors
cause both autism and obstetrical complications. The study conducted by Bolton
et al52
provided strong evidence in support of the shared risk hypothesis, as there
was an association between obstetric suboptimality and measures of autism
severity and familiality and the obstetric suboptimality scores in the
individuals with autism were highly correlated with that of their affected
siblings. In addition, probands with increased obstetric complications had
more extended family members with the broader autism phenotype, although this
finding was not replicated in a second study by Zwaigenbaum et
al.73 The
shared risk hypothesis was also supported by the findings in the Zwaigenbaum
et al study that indicated more obstetric adversity among unaffected
siblings of children with pervasive developmental disorders that had high
familial loading for the broader autism
phenotype.73

Limitations

Methodological limitations that have impaired the precision and validity of
results include small sample size, otherwise affected control groups (e.g.
Down syndrome), broad disease definition, and retrospective parental recall of
exposures. Of the 64 studies included in the review, only 19 had over 80%
power to detect a relative risk of 2 for an exposure with 10% prevalence.
Nineteen of the studies used broad diagnostic criteria resulting in the
possible inclusion of individuals with other autism-spectrum disorders, which
may limit the ability to detect associations due to aetiological
heterogeneity. Twenty-one studies assessed the exposure variables
retrospectively resulting in the high possibility of recall bias. However, the
use of medical records also has the limitation of being incomplete. Lastly,
the majority of studies included only univariate analyses and did not assess
potential confounding. These methodological weaknesses were also likely
sources of heterogeneity of effects across studies. Although significant
heterogeneity was observed for few factors, the test of heterogeneity lacked
power because the majority of the meta-analyses conducted were able to include
fewer than six studies and therefore variability in study characteristics was
lacking.

This meta-analysis has a few limitations. First, only published data were
used. Second, of the 64 studies reviewed, only 40 reported the data necessary
for inclusion in the meta-analysis. Within these 40 studies the investigators
did not report the necessary data for a meta-analysis on all factors examined.
Although 40 studies were included in the meta-analysis overall, for each
factor there were generally fewer than six studies included, limiting the
statistical power to detect heterogeneity across studies and potential effect
modification by study characteristics. Third, as a result of the rarity of
many of the exposures examined and the small sample sizes in many studies,
there were instances of zero cell counts within studies. The relatively small
addition of 0.5 to the cell counts may have had an impact on the overall
results because of the small sample sizes. Fourth, a few studies only reported
an effect estimate and an indication of whether the results were statistically
significant. In these cases, the confidence intervals were estimated based on
assumptions regarding the actual P-value (P = 0.05 if
significant, P = 0.50 if not significant). In the case of
statistically significant findings, these assumptions resulted in conservative
estimates of the true confidence intervals. Fifth, the tests of publication
bias were underpowered because of the limited number of studies in each
meta-analysis. Lastly, many studies simply examined all available prenatal
data using designs with methodological weaknesses and without a
priori hypotheses or knowledge about reproductive epidemiology. As a
result, significant associations observed because of chance are possible in
this meta-analysis.

The current review and meta-analysis was not restricted to studies with
particular methodological strengths. In addition, individual study
characteristics were examined in meta-regressions rather than assigning
studies aggregate quality scores. These strategies are consistent with the
recommendations proposed by the ‘Meta-Analysis of Observational Studies
in Epidemiology Group’ that advocated the use of broad inclusion
criteria for studies along with regression analyses to relate specific study
design characteristics to
outcome.97 This
maximises the amount of data available for review. In addition, different
methodological considerations are relevant for each exposure. However, the
increased probability for heterogeneity of results using the broad inclusion
criteria is important to note.

Twin studies and family aggregation studies have provided clear evidence
for the important role of genetics in autism
aetiology.6 The
difficulty in identifying environmental risk factors is likely a result of the
complex interactions between these factors and genetics in determining disease
susceptibility and the methodological considerations detailed above. Future
investigations of prenatal exposures should also collect DNA to study
potential gene–environment interactions.

Autism is a devastating condition with no known cure. The rising
prevalence, coupled with the severe emotional and financial impact on the
families, underscores the need for large, prospective, population-based
studies with the goal of elucidating the modifiable risk factors, particularly
those during the prenatal period.

Acknowledgments

We thank Ruifeng Li, MS (Harvard School of Public Health, Department of
Biostatistics) for providing additional statistical and programming support.
We also thank Alberto Ascherio, MD, DrPH (Harvard School of Public Health,
Departments of Epidemiology and Nutrition; Channing Laboratory, Department of
Medicine, Brigham and Women’s Hospital and Harvard Medical School) and
Janet Rich-Edwards, ScD (Harvard School of Public Health Department of
Epidemiology; Harvard Medical School) for their help and guidance in reviewing
the results and manuscript. We thank Dr. Tatjana Rundek, Yueh-Hsiu Mathilda
Chiu, and Handan Wand for their translations of articles published in
languages other than English.